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Home page / Research and projects / International projects and cooperation / 2019 / 2019 -2020 OECD Farm-Level Analysis Network: Drivers of farm performance

2019 -2020 OECD Farm-Level Analysis Network: Drivers of farm performance

Project No.:

TAD/DO/2017.47 (2019-2020)

Project title:

Drivers of farm performance

Class characteristics and structural dynamics, analysis base on Case Studies using an Empirical Approach

Sponsor:

OECD Trade and Agriculture Directorate

Duration:

2 years

Leader:

OECD Trade and Agriculture Directorate
Johannes Sauer, Technical University of Munich

Responsible person:

Ing. Vladimír Kostlivý, Dr.
Other investigators: Ing. Zuzana Fuksová, Ph.D.

Annotation:

The empirical project is part of OECD efforts to understand the impact of policies and other factors on productivity and environmental sustainability at the farm level. It is implemented in collaboration with the OECD Network for Farm-Level Analysis (FLA). Besides the twelve country cases considered till now, the Czech Republic as one of them, additional country cases may be envisaged in future work. Further work could also extend the empirical analyses to cover potential switches of farms between different technology classes over time as well as evaluating specific policy responses with respect to individual technology classes.

Timetable in 2019-20:

  • 3/19 APM network meeting: report incorporating all results and reflecting delegates comments on the report discussed at the May 2018 meeting [TAD/CA/APM/WP(2018)20] presentation
  • 5/19 FLA network meeting: final report presentation, further steps
  • 11/19 FLA network meeting: discussion of initial results and next steps
  • 5/20 FLA network meeting: discussion of results and next steps

Website:

https://www.oecd.org/agriculture/farm-level-analysis-network/

19th session of the Farm Level Analysis Network - May 2017:
https://www.oecd.org/agriculture/farm-level-analysis-network/Summary%20Record%20of%20the%2019th%20meeting%20of%20the%20FLA%20network.pdf

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OECD Farm-Level Analysis Network

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